Human factors approach to control contaminant concentrations in aircraft supply air from engine and APU bleed air and ground air sources, and in recirculated air being delivered to aircraft cabins for the optimization of user experience and energy consumption

ABSTRACT

An Environmental Control System includes a sensor, an air purification subsystem, and a controller in communication with the sensor and air purification subsystem. The sensor detects a contaminant in the air and generates a contaminant signal. The controller compares the contaminant signal to a predicted sensory response threshold. When the contaminant signal reaches the predicted sensory response threshold, the controller commands the air purification subsystem to alter a condition in the air.

BACKGROUND OF THE INVENTION

The present invention generally relates to apparatus and methods fortreatment of airstreams in an adaptive Environmental Control System(ECS) to remove contaminants.

ECSs of various types and complexity are used in military and civilairplanes, helicopter, and spacecraft applications. In aircraft forexample, airflow may be circulated to occupied compartments, cargocompartments, and electronic equipment bays. Air containing manypollutants such as particulate matter, aerosols, and hydrocarbons mayrange in humidity from dry (<2%) to very humid and may be delivered in aheated condition to the cabin from the ECS.

Aircraft occupants are not exposed to a single chemical in isolation,and the effects of co-exposures to multiple chemicals are poorlyunderstood. Exposure duration for crews can be 14+ hours. Crews canroutinely be assigned to work a 14 hour duty day without a break. Theduty day can be extended if there is a maintenance delay or weather.Some international crews are assigned to work a longer duty day. Thereare flight safety and security implications for not adequatelyprotecting pilots (who must perform cognitively-demandingsafety-sensitive flight duties) and cabin crew (who must maintain cabinsafety and security). Specifically, manufacturers are currently requiredto ensure that aircraft systems are designed to provide—in operation,under normal conditions and during any probable failure—“a sufficientamount of uncontaminated air to enable the crewmembers to perform theirduties without undue discomfort or fatigue, and to provide reasonablepassenger comfort.” It has been widely recognized by air accidentinvestigators, regulators, and pilot groups that flight safety can becompromised when pilots are exposed to oil-based contaminants in theventilation air entering from outside the aircraft through the mainengine bleeds or APU bleed or other air sources including groundsupplies and electric compressors. Requiring pilots to rely on theirnoses to identify the presence and location of bleed air contaminantsprolongs the exposure for the pilots and/or cabin occupants, dependingon the location of the contaminant source.

The industry accepted approach to verification of acceptability ofaircraft cabin air quality has been to gather air samples throughvarious forms of sample media to capture the range of contaminants thatmight be present. There are three US Environmental Protection Agency(EPA) methods that are accepted as guidance for sample collection andanalysis for volatile and semi-volatile compounds and for aldehydecompounds that may create odor and create irritancy.

The sample methodology is inadequate to fully characterize all compoundswith any given method, thus requiring the use of multiple methods. Theanalyst must also determine—based on equipment availability andlaboratory capability—which methods to use.

As can be seen, there may be an ongoing need to interpret real-time aircontaminant data and provide an indication of when the levels mayincrease beyond the range of acceptability to enable corrective action.

SUMMARY OF THE INVENTION

In one aspect of the present invention, an environmental control system(ECS) having contaminated air therein includes a sensor; an airpurification subsystem; and a controller in communication with thesensor and air purification subsystem; wherein the sensor detects acontaminant in the outside air supplied through the engines, APU orother air sources including ground supplies and electric compressors;and generates a contaminant signal; wherein the controller compares thecontaminant signal to a predicted sensory response threshold; whereinthe predicted sensory response threshold is based on one of odor,irritancy, mass, or a combination thereof; and when the contaminantsignal reaches the predicted sensory response threshold, commands theair purification subsystem to alter a condition in the contaminated air.

In another aspect of the present invention, a controller for anenvironmental control system (ECS) having a sensor and an airpurification subsystem communicates with the sensor and air purificationsubsystem; receives a contaminant signal from the sensor; compares thecontaminant signal to one of a contaminant concentration look up tableand a contaminant mass look up table; and based on the comparison,commands the air purification subsystem to alter a condition ofcontaminated air in the ECS.

In yet another aspect of the present invention, a method of controllingcontaminants in air in an environment includes creating a sampledatabase of the contaminants in the air; calculating a contaminantconcentration of a contaminant in the sample database; calculating apredicted sensory detection threshold of the contaminant; comparing thepredicted sensory detection threshold to one of a contaminantconcentration and contaminant mass in the air; and adjusting the airbased on the comparison.

These and other features, aspects and advantages of the presentinvention will become better understood with reference to the followingdrawings, description and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a block diagram of an environmental control system accordingto an exemplary embodiment of the present invention;

FIG. 1B is a block diagram of a controller that can be implemented inthe system of FIG. 1A according to an exemplary embodiment of thepresent invention;

FIG. 2A is a flow chart of a method of controlling contaminants in anenvironmental control system according to an exemplary embodiment of thepresent invention;

FIG. 2B and FIG. 2C is a flow chart of a method that can be implementedas part of the method of FIG. 2A;

FIG. 3A and FIG. 3B is a table depicting frequency of occurrence ofcontaminants in air samples according to an exemplary embodiment of thepresent invention;

FIG. 4A and FIG. 4B is a table depicting concentrations, at variouspercentiles, of contaminants in air samples according to an exemplaryembodiment of the present invention;

FIG. 4C and FIG. 4D is a table depicting isobutyene equivalentconcentrations, at various percentiles, of the contaminants in FIG. 4Aand FIG. 4B according to an exemplary embodiment of the presentinvention;

FIG. 5A and FIG. 5B is a table depicting predicted odor detectionthresholds of contaminants in air samples according to an exemplaryembodiment of the present invention;

FIG. 5C and FIG. 5D is a table depicting odor concentrations, at variouspercentiles, of contaminants in FIG. 5A and FIG. 5B according to anexemplary embodiment of the present invention;

FIG. 6A and FIG. 6B is a table depicting predicted sensory irritancydetection thresholds of contaminants in air samples according to anexemplary embodiment of the present invention;

FIG. 6C is a table depicting predicted sensory irritancy concentrations,at various percentiles, of contaminants in FIG. 6A and FIG. 6B accordingto an exemplary embodiment of the present invention;

FIG. 7 is a table summarizing predicted, combined contaminant odordetection thresholds; predicted, combined contaminant sensory irritancydetection thresholds; predicted, combined contaminant sensorythresholds; combined contaminant equivalence concentrations; andcombined contaminant mass;

FIG. 8 is a graph of probability of detectability, percentile of sampledatabase, and contaminant equivalence concentration;

FIG. 9 is a graph of probability of detectability, percentile of sampledatabase, and VOC mass.

DETAILED DESCRIPTION OF THE INVENTION

The following detailed description is of the best currently contemplatedmodes of carrying out the invention. The description is not to be takenin a limiting sense, but is made merely for the purpose of illustratingthe general principles of the invention, since the scope of theinvention is best defined by the appended claims.

Various inventive features are described below that can each be usedindependently of one another or in combination with other features.However, any single inventive feature may not address any of theproblems discussed above or may address only one of the problemsdiscussed above. Further, one or more of the problems discussed abovemay not be fully addressed by any of the features described below.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method, or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readable mediahaving computer readable program code embodied thereon.

Any combination of one or more computer readable storage media may beutilized. A computer readable storage medium is an electronic, magnetic,optical, or semiconductor system, apparatus, or device, or any suitablecombination of the foregoing. More specific examples (a non-exhaustivelist) of the computer readable storage medium would include thefollowing: a portable computer diskette, a hard disk, a random accessmemory (RAM), a read-only memory (ROM), an erasable programmableread-only memory (EPROM or Flash memory), a portable compact discread-only memory (CD-ROM), an optical storage device, a magnetic storagedevice, or any suitable combination of the foregoing. In the context ofthis document, a computer readable storage medium is any tangible mediumthat can store a program for use by or in connection with an instructionexecution system, apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable storage medium that can direct a computer, other programmabledata processing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablestorage medium produce an article of manufacture including instructionswhich implement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The present invention generally provides an environmental control system(ECS) that can continuously adapt to changing contaminants—both in kindand degree—in contaminated air in the ECS. The contaminated air mayinclude outside air entering the ECS through engines or APU, or otherair sources including ground supplies and electric compressors, as wellas recirculating air in the ECS. A controller of the ECS may receivecontamination signals from one or more sensors that sense one or morecontaminants in the contaminated air. The sensors may also sense totalmass of the contaminants—without regard to the specific contaminantsbeing sensed.

One or more of these contamination signals can then be compared againsta predicted sensory response threshold and/or an average sensoryresponse threshold. If the threshold is exceeded, the controller maysend control signals to an air purification subsystem of the ECS toalter, for example, fan speed, air flow rate, or modulating theoperating rate of an air purification system, or opening and closingvalves to such an air purification system in the outside air and/orrecirculating air entering, for example, an environment. The thresholdsof the supply air, the recirculated air, and the cabin air may bedifferent. The method of determining thresholds can be the same for eachair source or location. The threshold of the outside air divided by itssensory limit times the flow rate, plus the threshold of therecirculated air divided by its sensory limit time the flow ratedetermines the total threshold of the cabin air. The environment may bea cabin of an aircraft or other vehicle, or other space such as abuilding intended to be occupied by humans. Once the contaminationsignal(s) drops below the total threshold of the cabin air, thecontroller may discontinue commanding the alteration of the contaminatedair.

Generally, the present invention can include determining one or moresensory thresholds for contaminants, such as odor detection thresholdsand/or sensory irritancy thresholds and/or mass thresholds. Based on oneor more of the thresholds, the present invention may then predict one ormore predicted sensory response thresholds. The predicted sensoryresponse threshold can then be used to continuously compare it againstactual contaminant levels, and thus enable continuous control ofcontaminants in the environment.

FIG. 1 is a block diagram of an ECS 10 according to an exemplaryembodiment of the present invention. The ECS 10 may include a controller11, such as a computer having a processor and a memory, in continuous orintermittent communication with an air purification subsystem 13 and oneor more sensors 12. The sensors 12 may be positioned in various pointsthroughout the ECS to sense contaminants in the outside air suppliedthrough engine or APU bleeds, or other air sources including groundsupplies and electric compressors, and/or recirculating air in the ECSand/or, in particular, an environment 14, such an aircraft cabin. Thecontaminants in the ECS may include, for example, OVCs and/or SVOCsand/or ultrafine particles (UFPs).

The sensor 12 can be any sensor capable of sensing the anticipatedcontaminants in the contaminated air. One or more of the sensors cansense the identity and amount of the individual contaminants in thecontaminant air. In addition, one or more sensors can sense the mass ofthe contaminants without regard to the specific identity of theindividual contaminants. For example, to sense individual contaminants,the sensor 12 may be a photoionization detector (PID), such as a PID byRAE Systems of San Jose, Calif. To sense total mass of contaminants, thesensor may also be a PID. These types of sensors and their operation isdescribed in the PID Handbook (Third Edition), by RAE Systems Inc.,which is incorporated herein by reference in its entirety.

An example configuration of multiple sensors in an ECS that can beemployed in the present invention is shown, for example, in US patentapplication, entitled “Aircraft Environmental Control System ThatOptimizes the Proportion of Outside Air From Engines, APUs, Ground AirConditioning Units and the Recirculated Cabin Air to Maintain OccupantComfort and Maximize Fuel Economy,” filed concurrently with thisapplication and incorporated herein by reference in its entirety.

The air purification subsystem 13 may include various coolers, fans, andfilters to alter the contaminated air. An example of an air purificationsubsystem that can be employed in the present invention is shown, forexample, in US patent application, entitled “Aircraft EnvironmentalControl System That Optimizes the Proportion of Outside Air FromEngines, APUs, Ground Air Conditioning Units and the Recirculated CabinAir to Maintain Occupant Comfort and Maximize Fuel Economy,” filedconcurrently with this application and incorporated herein by referencein its entirety.

FIG. 1B is a functional block diagram of the controller 11 according toan exemplary embodiment of the present invention. The controller 11include a processor (not shown) and a memory (not shown) that can storeinstructions to be executed by the processor to implement a method ofremoving contaminants from a space to be occupied by humans, such as thecabin of an aircraft, according to the present invention. The controller11 may receive contamination signals from sensor(s) 12 a which may sensecontaminants from, for example, a cabin filter, a filter to a mixmanifold, an ECS pack to a mix manifold, and the mix manifold to thecabin. The controller 11 may also receive contamination signals fromsensor(s) 12 b which may sense contaminants from bleed air.

The controller 11 may then compare the contamination signals to acontaminant concentration look up table 15 a that may haveinformation/data of contaminant concentration equivalents versuspercentile of a sample database. The controller 11 may, in addition toor in lieu of the foregoing comparison, compare contamination signals toa contaminant mass look up table 15 b that may have information/data oftotal mass of contaminants versus percentile of a sample database thatmay or may not the be same sample database in look up table 15 a.

Based on the foregoing comparison(s), the controller 11 may then commanda valve 13 a to alter valve opening/closing and thereby alter a flow ofoutside air. Also, in addition to or in lieu of the foregoing command,the controller may command a fan 13 b to alter a fan speed ofrecirculated air. Alternatively, the response of the controller may beto modulate an air purification device, increasing or decreasing itspower to effect the desired change in air contaminant concentrations

Either alone or in combination with commanding the valve 13 a and thefan 13 b, the controller may command an outflow valve 13 c to open orclose. The valve 13 c may enable combined outside and recirculated airto enter the cabin as cabin air 14 c.

FIG. 2A is a flow chart that depicts general exemplary steps of a method20, which may be implemented by a controller, such as controller 11, ofremoving contaminants from an environment such as an aircraft cabin.FIG. 2B is a flow chart that depicts more specific steps that can beemployed, according to an exemplary embodiment, to implement at leastsome of the general steps shown in FIG. 2A.

In FIG. 2A, the method 20 may generally include a step 21 fordetermining a frequency of occurrence of individual contaminants insamples of contaminated air that are expected to be present in theenvironment 14. In the example of an aircraft cabin, the samples may beoutside air and engine bleed air.

A step 22 may generally include calculating individual contaminantconcentration in the samples at various sample population percentiles,such as the 75th, 90th, 95th, and 99th percentiles, as well ascalculating a mean concentration. This may include calculatingindividual “concentration equivalents” which refer to the concentrationsof a calibration or equivalent compound (such as isobutylene) used by asensor (such as a PID sensor by RAE Systems) to convert concentrationsof different contaminants to concentrations of one calibration orequivalent compound, as further described in the PID Handbook (ThirdEdition), by RAE Systems Inc.

A step 23 may generally include calculating predicted, individualcontaminant odor detection thresholds (i.e., responses) at varioussample population percentiles, which can be the same or differentpercentiles as the contaminant concentration equivalents above, as wellas a mean odor threshold.

A step 24 may generally include calculating predicted, individualcontaminant sensory irritancy detection thresholds (i.e., responses) atvarious sample population percentiles, which can be the same ordifferent percentiles as the contaminant concentration equivalentsand/or odor thresholds above, as well as a mean irritancy threshold.

A step 25 may generally include, using the foregoing predicted sensorydetection threshold(s)—i.e., odor thresholds and/or irritancythresholds—for calculating predicted, combined contaminant sensorythresholds (i.e., responses) at various sample population percentiles,which can be the same or different percentiles as the contaminantconcentration equivalents and/or odor thresholds and/or irritancythresholds above, as well as a mean sensory threshold. The predicted,combined contaminant sensory thresholds may be average sensory responses(i.e., thresholds).

As can be appreciated, calculating predicted, combined contaminantsensory thresholds 25 need not be based on only odor and/or irritancythresholds. Other sensory thresholds, such as contaminant massthresholds, can be used to calculate the predicted, combined contaminantsensory thresholds. It can also be appreciated that step 25 need not beutilized in method 20 when, for example, a single predicted sensorydetection threshold is used for the below described comparison to acontamination signal.

A step 26 may generally include comparing one or more predicted,combined contaminant sensory thresholds to one or more contaminantsignals from one or more sensors. The contaminant signals can be basedon a combination or mixture of the individual contaminant concentrationequivalents determined in step 22. Step 26 may also include a comparisonof the foregoing to a probability of contaminant detection by anoccupant in an environment, such as environment 14.

A step 27 may generally include adjusting one or more of the contaminantair sources based on the foregoing comparison. The adjusting may occurprior to or when the contaminants reach a threshold of probability ofcontaminant detection.

FIG. 2B depicts exemplary sub-steps of the general steps 21 to 26, andsuch sub-steps are described below.

Referring again to FIG. 2A, step 21 may include collecting samples ofcontaminated air that may be expected to enter the environment 14. Thesamples may be collected at different times and from different sourcesto create a sample database. For example, in the context of an aircraftcabin, the present inventors used for experimental, exemplary purposesdifferent contaminated air sources that included engine air and APUbleed air. In some instances, the samples came from engine test cells.In other instances, the samples came from engines and APUs installed onaircraft. Further, the experimental samples were acquired between 1996and 2013; however, the present invention envisions a time frame that islonger or shorter than seventeen years. The total number of experimentalsamples exceeded two hundred; however, the present invention envisionsmore or less than two hundred samples.

In the experimental database, there was significant data scatter. Someof that scatter could be related to environmental conditions around thetest area. The scatter could also be due to variation in sampling andlaboratory analysis over the seventeen year period. This databaseindicates that there may be hundreds of different compounds and/orcontaminants present in any given sample.

Step 21 may include steps 21 a, 21 b, and 21 c shown in FIG. 2B and FIG.2C. In step 21 a, a total sample size for each contaminant may bedetermined (i.e., total number of samples tested for a contaminant ofinterest, regardless of whether the contaminant of interest waspresent). In step 21 b, a non-zero sample size (i.e., number of sampleswhere the contaminant of interest was present) for each contaminant maybe determined. In step 21 c, a frequency of occurrence for eachcontaminant can calculated by taking the ratio of non-zero samples tototal samples. These results are shown in FIG. 3A and FIG. 3B.

In step 21 d, as shown in FIG. 3A and FIG. 3B, the contaminants can beordered by importance, starting from the highest frequency of occurrenceand ending at the lowest frequency—for purposes of illustration. Othercharacteristics might be used to determine importance, such as sensoryperception. One example is acrolein because it is extremely irritatingat very low concentration.

FIG. 3 A and FIG. 3B lists (for illustration purposes) sixty four of themost frequently occurring compounds in bleed air. It can be seen fromFIG. 3A and FIG. 3B that only ten compounds occur in more than 60% ofthe samples. However, other contaminants, such as tricresylphosphateisomers (TCP), can be considered significant and included in thedatabase, even if they do not occur frequently, due to concerns aboutthe effects of long term exposure by humans.

As further described below, assessing the contaminants as shown in FIG.3A and FIG. 3B can be used in the method 20 to interpret real-time aircontaminant data from sensors, and provide an indication of when thelevels may increase significantly enough to fall outside the range ofnormal distribution of the data. Identifying the level that fallsoutside levels normally encountered (i.e., thresholds) can be used toprovide an early warning of a pending maintenance action in oneinstance. In another instance, identifying levels that fall outside anorm can be used for controlling outside air-flow and the airpurification subsystem 13.

Referring to FIG. 2B and FIG. 2C and FIG. 4A and FIG. 4B, in step 22,for the contaminants of interest determined in step 21, individualcontaminant concentrations can be calculated at various samplepopulation percentiles in step 22 a. In an exemplary embodiment, theindividual concentrations for the individual contaminants in FIG. 3 Aand FIG. 3B were calculated at the mean of the database, and at the75th, 90th, 95th, and 99th percentiles. Those contaminantconcentrations—in both ug/m³ and ppmV—are presented in FIG. 4A and FIG.4B.

Referring to FIG. 2B and FIG. 4C and FIG. 4D, in step 22 b, individualcontaminant “concentration equivalents” can be calculated from theindividual contaminant concentrations in step 22 a. In an exemplaryembodiment, the individual concentration equivalents for the individualcontaminants in FIG. 3A and FIG. 3B were calculated at the mean of thedatabase, and at the 75th, 90th, 95th, and 99th percentiles. Thosecontaminant concentration equivalents are presented in FIG. 4C and FIG.4D.

The calculation of contaminant concentration equivalents can beperformed in various ways, depending on the specific sensor(s) 12 used.In the illustrative experiments by the inventors herein, isobutylene PIDsensors by RAE Systems were used. Therefore, sensors were calibrated toisobutylene, and the actual concentrations of the actual contaminantssensed were all converted to isobutylene equivalent concentrations(ppm-V), as shown in FIG. 4B. The conversion is obtained by the actualconcentration divided by a correction factor for the contaminant asestablished by RAE Systems and replicated in the “Factor fordenominator” column in FIG. 4C and FIG. 4D.

Referring to FIG. 2B and FIG. 2C and FIG. 5A and FIG. 5B, a step 23—forcalculating a predicted odor detection threshold for one or more of thecontaminants from step 21—can include steps 23 a, 23 b, 23 c, and 23 din an exemplary embodiment.

Step 23 a can include determining odor detection thresholds (ODTs) forone or more of the contaminants of interest from step 21. In oneexample, this can be accomplished experimentally.

In another example, step 23 a can include looking up previouslydetermined (i.e., published) ODTs for one or more of the contaminants ofinterest from step 21. For example, step 23 a can include obtaining ODTsfrom Devos et al., (1990) Standardized human olfactory thresholds.Oxford: IRL Press, which is incorporated by reference herein in itsentirety.

In step 23 b, log 10 values of the reciprocals of the ODTs (for example,those from Devos 1990 above) can be calculated in volume, and in step 23c can be calculated in mass. The results are shown in FIG. 5A and FIG.5B. The volume ODTs in units of ppm can be used to calculate predictedsensory thresholds or average sensory responses and then for eventualcomparison with data of concentration equivalents in the contaminatedair, as described below. Likewise, the mass ODTs in units of ug/m³ canbe used to calculate predicted sensory thresholds and then for eventualcomparison with data of mass of contaminants in the contaminated air, asdescribed below.

In step 23 d, for one or more of the contaminants of interest, apredicted, single contaminant odor detection (OD) ratio (e.g.,threshold) may be calculated wherein the numerator is the ppmcontaminant concentration from FIG. 4A and FIG. 4B and the denominatoris the ppm odor threshold from FIG. 5A and FIG. 5B. These ratios can becalculated at various sample population percentiles, which can be thesame or different as the percentiles in FIG. 4A and FIG. 4B, as well asa mean. The results are shown in FIG. 5C and FIG. 5D. It can be notedthat the contaminants for which ODTs and/or OD ratios are determinedneed not be identical to all of the contaminants in step 21.

In step 23 e, the odor detection ratios from step 23 d can be convertedto dose addition ratios, as shown in FIG. 5A with the column headings“DA.” The dose addition method is described in Fox, “Assessing AircraftSupply Air to Recommend Compounds for Early Timely Warning ofContamination”, Dissertation, April 2012 which is incorporated byreference herein in its entirety.

Also, in step 23 e, predicted, mixed contaminant odor detection ratios(e.g., thresholds) can then be calculated. These ratios are the sum ofthe dose addition ratios of the individual contaminants according to thefollowing:

$\begin{matrix}{{\frac{C_{1}}{T_{1}} + \frac{C_{2}}{T_{2}} + \ldots + \frac{C_{n}}{T_{n}}} = {{Qmix}\mspace{14mu}{Dose}\mspace{14mu}{Addition}\mspace{14mu}{Odor}}} & (1)\end{matrix}$where C is the individual contaminant concentration in ppmV from FIG. 4Aand FIG. 4B at a selected percentile and T is the odor detectionthreshold for that contaminant in ppmV for the dose addition (DA) fromFIG. 5C and FIG. 5D at the same selected percentile.

The predicted, mixed contaminant dose addition ratios can be at variousratios, which can be at the same or different percentiles as in theindividual dose addition ratios. These mixed ratios are shown at thebottom of FIG. 5C and FIG. 5D. As further described below, the mixedodor ratios are later used provide a predicted combined contaminantsensory threshold (i.e., average sensory response) for the mixture ofcontaminants of interest.

Without intending to limit the scope of the present invention, it isnoted that the relationship between the concentrations of contaminantsin a mixture to predicted odor is believed to be similar to therelationship of mixture contaminant concentration to the predictedsensory irritancy. This is described in Cometto-Muñiz, J. E., Cain, W.S., Abraham, M. H., & Gola, J. M. R. (1999). Chemosensory detectabilityof 1-butanol and 2-heptanone singly and in binary mixtures. Physiology &Behaviour, 67, 269-276. doi: 10.1016/S0031-9384(99)00074-8, which isincorporated herein by reference in its entirety. The predicted sensoryirritancy of a mixture of contaminants has been found to have anadditive effect on sensory irritancy, but not have a hypo-additiveeffect or a hyper-additive effect (Cometto-Muñiz et al., 1999). A strongcorrelation between dose additivity of a mixture on predicted odordetection levels half-way between chance and perfect detection has beenreported at a probability level of 0.3 (0.00<P<0.35). Cometto-Muñiz, J.E., Cain, W. S., & Abraham, M. H. (2003). Dose-addition of individualodorants in the odor detection of binary mixtures. Behavioural BrainResearch, 138, (1), 95-105. doi: 10.1016/S0166-4328(02)00234-6 which isincorporated herein by reference in its entirety. A strong correlationbetween dose additively at sensory irritancy detection levels half-waybetween chance and perfect detection has been reported at a probabilitylevel of 0.6 (0.55<P<0.65) by Cometto-Muñiz et al. (2003).

Therefore, like the calculation of odor detection thresholds for thecontaminants of interest, the method 20 includes steps for calculatingsensory irritancy thresholds for the contaminants of interest—throughsteps 24 a, 24 b, 24 c, 24 d, 24 e and 24 f according to an exemplaryembodiment.

Step 24 a can include determining sensory irritancy detection thresholds(SIDTs) for one or more of the contaminants of interest from step 21.For example, this can be accomplished experimentally. It can be notedthat the contaminants for which SIDTs are determined need not beidentical to all of the contaminants in step 21 and/or all of thecontaminants in step 23.

In another example, step 24 a can include looking up previouslydetermined (i.e., published) SIDTs for at least one of the contaminantsof interest from step 21 and/or step 23. For example, step 24 a caninclude obtaining SIDTs from Abraham, M. H., Sanchez-Moreno, R.,Gil-Lostes, J., Acree, W. E., Jr., Cometto-Muñiz, J. E., & Cain, W. S.(2010). The biological and toxicological activity of gases and vapors.Toxicology in Vitro, 24(2), 357-362. doi:10.1016/j.tiv.2009.11.009 whichis incorporated herein by reference in its entirety.

In step 24 b, log 10 values of the reciprocals of the SIDTs (forexample, those from Abraham 2010 above) can be calculated in volume, andin step 24 c can be converted from volume to mass. The results are shownin FIG. 6A. For example, the following equation can be used to calculatethe conversion:Y mg/m³=(X ppm)(molecular weight of contaminant)/24.45  (2)

The volume SIDTs in units of ppm can be used to calculate predictedsensory thresholds or average sensory responses and then for eventualcomparison with data of concentration equivalents in the contaminatedair, as described below. Likewise, the mass SIDTs in units of ug/m³ canbe used to calculate predicted sensory thresholds and then for eventualcomparison with data of mass of contaminants in the contaminated air, asdescribed below.

In step 24 d, for one or more of the contaminants of interest, apredicted, single contaminant sensory irritancy detection (SID) ratio(e.g., threshold) may be calculated wherein the numerator is the ppmcontaminant concentration from FIG. 4A and FIG. 4B and the denominatoris the ppm odor threshold from FIG. 6A and FIG. 6B. These ratios can becalculated at various sample population percentiles, which can be thesame or different as the percentiles in FIG. 4A and FIG. 4B, as well asa mean. It can be noted that the contaminants for which SIDTs and/or SIDratios are determined need not be identical to all of the contaminantsin step 21.

In step 24 e, one or more of the odor detection ratios from step 24 dcan be converted to dose addition ratios, as shown in FIG. 6C. Theseratios can be calculated at various percentiles, which can be the sameor different as the percentiles in FIG. 4A and FIG. 4B, as well as amean. The results are shown in FIG. 6C.

Also, in step 24 e, predicted, mixed contaminant, sensory irritancydetection ratios (e.g., thresholds) can then be calculated. These ratiosare the sum of the dose addition ratios of the individual contaminantsfrom step 24 e according to the following:

$\begin{matrix}{{( {\frac{C_{1}}{T_{1}} + \frac{C_{2}}{T_{2}} + \ldots + \frac{C_{n}}{T_{n}}} ) \otimes 0.0005} = {{Qmix}\mspace{14mu}{Dose}\mspace{14mu}{Addition}\mspace{14mu}{Sensory}\mspace{14mu}{Irritancy}}} & (3)\end{matrix}$where C is the contaminant concentration in ppmV from FIG. 4A and FIG.4B at a selected percentile and T is the sensory irritancy threshold forthat contaminant in ppmV from FIG. 6A and FIG. 6B. The results are shownat the bottom of FIG. 6C.

In step 24 f, the above dose addition equation (3) for sensory irritancycan include an adjustment based on qualitative experience. A factor of0.0005 is utilized in this exemplary embodiment.

The method 20 continues to a step 25 wherein one or more predictedsensory thresholds, such as the predicted odor detection threshold fromstep 23 and/or the predicted sensory irritancy detection threshold fromstep 24, can but need not be combined to provide a predicted, combinedcontaminant sensory threshold or average sensory threshold (i.e.,response) for the mixture of contaminants of interest. That averagesensory threshold can be at various sample population percentiles, suchas the same percentiles used in step 22 and/or step 23 and/or step 24.

The average sensory threshold can be calculated in step 25 by summingone-half of the mixed predicted odor ratio (from FIG. 5C and FIG. 5D)and one-half of the mixed irritancy ratio (from FIG. 6C), at the samepercentile for each ratio. The results are shown in FIG. 7. As can beappreciated, the average sensory threshold or response can be based onthresholds other than odor and/or irritancy.

In step 26, there can be sub-steps 26 a, 26 b, and 26 c according to anexemplary embodiment.

In step 26 a, a comparison can be made between probability ofcontaminant detection versus contaminant percentile in database. Theprobability of contaminant detection can include one or more predictedsensory thresholds or ratios—for a single contaminant or a mixture ofcontaminants. For example, they can be one or more of the predictedmixed odor ratio, the predicted mixed irritancy ratio, and the averagesensory response. A probability of one (1) can be considered equivalentto a 100% probability of detection by an occupant in an environment. Thecontaminant percentile may be the 75th, 90th, 95th, and 99thpercentiles, as well as the mean, for example.

Step 26 a may further include a comparison of contaminant concentrationequivalents versus contaminant percentile in database. For example, asin the experiments described above, the concentration equivalents can beisobutylene equivalents.

The comparisons in step 26 a can be depicted in tabular form, as in FIG.7. They may also be shown graphically, as in FIG. 8.

In step 26 b, and in reference to FIG. 8, a determination can be made ofthe sample population percentile at which one or more of the predictedmixed odor ratio, the predicted mixed irritancy ratio, the averagesensory response, and the concentration equivalents has a probability ofdetection of one (1). This can also include the contaminant massdescribed below.

In step 26 c, comparisons can be made as in step 26 a, except that totalcontaminant mass can be compared instead of concentration equivalents.The comparisons in step 26 c can be depicted in tabular form, as in FIG.7. They may also be shown graphically, as in FIG. 9.

In step 27, adjustments to the outside air and/or recirculating air maybe made based on the comparisons made in step 26. In some embodiments,the controller 11 can command adjustments to the air purificationsubsystem 13.

These adjustments may, in various embodiments be based on the sensedconcentration equivalents reaching or exceeding a level that is below a100% probability of contaminant detection—or, in other words, reachingor exceeding a predicted sensory response threshold.

For example, based on the comparisons depicted in FIG. 8—and inparticular the mixed predicted odor ratio, the mixed predicted irritancyratio, and average sensory response—adjustments may be made at about the0.85 percentile or less. This is because the probability of detection isless than about 1.0 (or 100%) up to about the 0.80 percentile for thepredicted sensory response threshold—e.g., the mixed predicted odorratio, the mixed predicted irritancy ratio, and/or average sensoryresponse. Thus, in the example of FIG. 8, the controller 11 may commandadjustments to the air purification subsystem 13 when the controllerreceives a contamination signal that a predicted sensory threshold hasbeen reached—e.g., an isobutylene concentration equivalent for the mixedcontaminants has reached about the 0.80 percentile—about 0.009 ppm.

In another example, based on the comparisons depicted in FIG. 9,adjustments may be made at about the 0.825 percentile or less than the0.825 percentile. This is because the probability of detection is lessthan about 1.0 (or 100%) up to about the 0.825 percentile. In theexample of FIG. 9, the controller 11 may command adjustments to the airpurification subsystem 13 when the controller receives a contaminationsignal that total mass for the mixed contaminants has reached about the0.825 percentile—about 450 ug/m³.

It should be understood, of course, that the foregoing relates toexemplary embodiments of the invention and that modifications may bemade without departing from the spirit and scope of the invention as setforth in the following claims.

We claim:
 1. An environmental control system (ECS) having contaminantsin air therein, comprising: a sensor; an air purification subsystem; anda controller in communication with the sensor and air purificationsubsystem; wherein the sensor: detects a contaminant in the air; andgenerates a contaminant signal; wherein the controller: compares thecontaminant signal to a predicted sensory response threshold; whereinthe predicted sensory response threshold is based on a plurality ofcontaminant sample population percentiles; wherein the predicted sensoryresponse threshold is below a dose addition sensory response of 1.0; andwhen the contaminant signal reaches the predicted sensory responsethreshold, commands the air purification subsystem to alter a conditionin the air containing the contaminant.
 2. The ECS of claim 1, whereinthe air containing contaminants includes outside air entering the ECSthrough engine and APU bleeds, or other air sources including groundsupplies and electric compressors, and recirculated air circulatingthrough the ECS.
 3. The ECS of claim 1, wherein the contaminant signalis based on one of odor, irritancy, mass, and a combination thereof. 4.The ECS of claim 1, wherein the contaminant signal is based on a sampleof anticipated contaminants in the air.
 5. The ECS of claim 1, whereinthe predicted sensory response threshold is based on a percentilepopulation of anticipated contaminants in the air.
 6. The ECS of claim1, wherein the predicted sensory response threshold is based on one ofan odor threshold, an irritancy threshold, a mass threshold, and acombination thereof.
 7. The ECS of claim 1, further comprising a valve,a mix manifold, and a fan in communication with the controller.
 8. TheECS of claim 1, wherein sensor senses one of outside air entering theECS, recirculated air circulating through the ECS, and a combinationthereof.